Evaluation of the potentials of new scientific developments for commercial poultry breeding

MAGE: metafounders-assisted genomic estimation of breeding value, a novel additive-dominance single-step model in crossbreeding systems

MOTIVATION

Utilizing both purebred and crossbred data in animal genetics is widely recognized as an optimal strategy for enhancing the predictive accuracy of breeding values. Practically, the different genetic background among several purebred populations and their crossbred offspring populations limits the application of traditional prediction methods. Several studies endeavor to predict the crossbred performance via the partial relationship, which divides the data into distinct sub-populations based on the common genetic background, such as one single purebred population and its corresponding crossbred descendant. However, this strategy makes prediction inaccurate due to ignoring half of the parental information of crossbreed animals. Furthermore, dominance effects, although playing a significant role in crossbreeding systems, cannot be modeled under such a prediction model.

RESULTS

To overcome this weakness, we developed a novel multi-breed single-step model using metafounders to assess ancestral relationships across diverse breeds under a unified framework. We proposed to use multi-breed dominance combined relationship matrices to model additive and dominance effects simultaneously. Our method provides a straightforward way to evaluate the heterosis of crossbreeds and the breeding values of purebred parents efficiently and accurately. We performed simulation and real data analyses to verify the potential of our proposed method. Our proposed model improved prediction accuracy under all scenarios considered compared to commonly used methods.

AVAILABILITY AND IMPLEMENTATION

The software for implementing our method is available at https://github.com/CAU-TeamLiuJF/MAGE.

Improving production efficiency in the presence of genotype by environment interactions in pig genomic selection breeding programmes

We simulated a genomic selection pig breeding schemes containing nucleus and production herds to improve feed efficiency of production pigs that were cross-breed. Elite nucleus herds had access to high-quality feed, and production herds were fed low-quality feed. Feed efficiency in the nucleus herds had a heritability of 0.3 and 0.25 in the production herds. It was assumed the genetic relationships between feed efficiency in the nucleus and production were low (r_g  = 0.2), medium (r_g  = 0.5) and high (r_g  = 0.8). In our alternative breeding schemes, different proportion of production animals were recorded for feed efficiency and genotyped with high-density panel of genetic markers. Genomic breeding value of the selection candidates for feed efficiency was estimated based on three different approaches. In one approach, genomic breeding value was estimated including nucleus animals in the reference population. In the second approach, the reference population was containing a mixture of nucleus and production animals. In the third approach, the reference population was only consisting of production herds. Using a mixture reference population, we generated 40-115% more genetic gain in the production environment as compared to only using nucleus reference population that were fed high-quality feed sources when the production animals were offspring of the nucleus animals. When the production animals were grand offspring of the nucleus animals, 43-104% more genetic gain was generated. Similarly, a higher genetic gain generated in the production environment when mixed reference population was used as compared to only using production animals. This was up to 19 and 14% when the production animals were offspring and grand offspring of nucleus animals, respectively. Therefore, in genomic selection pig breeding programmes, feed efficiency traits could be improved by properly designing the reference population.

A crossbred reference population can improve the response to genomic selection for crossbred performance

Background

Breeding goals in a crossbreeding system should be defined at the commercial crossbred level. However, selection is often performed to improve purebred performance. A genomic selection (GS) model that includes dominance effects can be used to select purebreds for crossbred performance. Optimization of the GS model raises the question of whether marker effects should be estimated from data on the pure lines or crossbreds. Therefore, the first objective of this study was to compare response to selection of crossbreds by simulating a two-way crossbreeding program with either a purebred or a crossbred training population. We assumed a trait of interest that was controlled by loci with additive and dominance effects. Animals were selected on estimated breeding values for crossbred performance. There was no genotype by environment interaction. Linkage phase and strength of linkage disequilibrium between quantitative trait loci (QTL) and single nucleotide polymorphisms (SNPs) can differ between breeds, which causes apparent effects of SNPs to be line-dependent. Thus, our second objective was to compare response to GS based on crossbred phenotypes when the line origin of alleles was taken into account or not in the estimation of breeding values.

Results

Training on crossbred animals yielded a larger response to selection in crossbred offspring compared to training on both pure lines separately or on both pure lines combined into a single reference population. Response to selection in crossbreds was larger if both phenotypes and genotypes were collected on crossbreds than if phenotypes were only recorded on crossbreds and genotypes on their parents. If both parental lines were distantly related, tracing the line origin of alleles improved genomic prediction, whereas if both parental lines were closely related and the reference population was small, it was better to ignore the line origin of alleles.

Conclusions

Response to selection in crossbreeding programs can be increased by training on crossbred genotypes and phenotypes. Moreover, if the reference population is sufficiently large and both pure lines are not very closely related, tracing the line origin of alleles in crossbreds improves genomic prediction.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0155-z) contains supplementary material, which is available to authorized users.

Maximizing genetic response in crossbreds using both purebred and crossbred information

A combined crossbred and purebred selection (CCPS) method, i.e. using crossbred and purebred information, was proposed to achieve genetic response in crossbred animals. Selection index theory was applied to establish a CCPS index. The CCPS was compared with pure-line selection (PLS) and crossbred selection (CS) methods. The genetic correlation between purebred and crossbred performance (rpc) and crossbred heritability (hc2) are crucial factors in the comparison. The CCPS is always better than PLS or CS when a fixed number of purebred progeny is tested. With a fixed total number of purebred and crossbred tested progeny, CCPS is only worse than PLS for very high values of rpc (>0·8). Superiority of CCPS over PLS increases and over CS decreases with decreasing rpc. The larger hc2 is, relative to purebred heritability (hc2 the more response CS and CCPS will achieve. The robustness of CCPS against inappropriate assumptions on rpc and hc2 values was investigated. The expected response is always an overestimate, and the actual response is smaller than the optimal response when rpc is assumed one but the true rpc is smaller. The difference between actual and optimal response increases as rpc decreases but it is small for large rpc values (e.g. <3% for rpc >0·7). The expected response is smaller than the actual response when rpc is large and hc2> hp2 Finally, the actual response to CCPS is larger than the optimal response to PLS for positive values for rpc. The main conclusions are: (1) CCPS method is optimal for obtaining genetic response in crossbreds; and (2) CCPS with inappropriate assumptions on rpc and hc2 values (e.g. recognizing crossbreds as purebreds) achieves more genetic response than PLS for common values of rpc and crossbred heritability.

Discounted expressions of traits in broiler breeding programs

The commercially grown broiler usually is a crossbred from specialized purebred sire and dam lines. The position of a purebred line in the crossbreeding system influences its genetic contribution to expression of productive and reproductive performance at different stages of the production column and, thus, influences the breeding goal for a given line. In broiler breeding, cumulative discounted expressions (CDE) should be considered to define breeding goals for multi-trait selection. In the present study, a systematic design for the application of discounted gene flow methodology to derive CDE for production and reproduction traits in broiler breeding was developed. Factors considered as influencing the magnitude of CDE were: crossbreeding system (two-way, three-way, and four-way cross), selection scheme (with and without progeny testing and intensity of selection), selection path, trait (production at commercial stage and reproduction at either nucleus or multiplier stage), interest rate, and time horizon for evaluation. Performance data from a commercial breeding stock were applied in the analysis. Results indicated that levels of CDE were significantly affected by all factors studied. The more that pure lines were included in the crossbreeding system, the lower the CDE for a particular selection path. However, the summation of all selection paths did not differ much among crossbreeding systems. Progeny testing decreased CDE by increasing generation intervals. The CDE for reproduction traits were higher than those for production traits mainly as a result of earlier expression of the reproduction traits.

Comparison of selection based on phenotype, selection index and best linear unbiased prediction using data from a closed broiler line

1. Selection based on three methods of estimating breeding values, Best Linear Unbiased Prediction (BLUP), selection index (SI), and phenotype (SP) were compared for three traits, juvenile body weight (JW), percentage breast meat yield (BM) and hen-day rate of egg production (EP) using records provided by a commercial broiler breeding company. 2. Product moment correlations were calculated between breeding values estimated by each method and averaged across sexes. A mean correlation of 0.69 was obtained between selection on SP and BLUP for JW. Mean correlations of 0.88 and 0.68 and 0.87 were obtained between SI and BLUP for the traits JW, EP and BM, respectively. 3. A mean estimated genetic response of 77.7% was obtained with SP for JW relative to BLUP in the absence of restrictions on the selection of close relatives. Estimated genetic responses of 90.7%, 66.9% and 88.4% were obtained by SI relative to BLUP for JW, EP and BM, respectively. 4. Applying restrictions on the selection of close relatives resulted in slight decreases in estimated responses but not in the respective ranking of the selection methods. 5. The results indicate that BLUP could provide commercial breeders with increased selection responses compared to index selection, in particular for traits of low heritability and where relatively few animals possess performance records.

Genetic markers linked to quantitative traits in poultry

This study utilized DNA fingerprints and crosses of two genetically distinct lines of layer-type chickens to identify genetic markers linked to quantitative trait loci (QTL). In phase I, backcross (BC1) hens were separately ranked for each of eight traits and then blood pools were produced in groups along each phenotypic distribution. The DNA was isolated from the blood pools and used in a gradient analysis to screen for DNA fingerprint bands that exhibited intensity gradients associated with the phenotypic traits. To identify linkage of bands with QTL and to estimate band effects, F2 progeny were produced in phase II from the phase I BC1 population. A single-trait animal model was used for analysis of associations of all individual DNA fingerprint bands of sires and their progeny phenotypic performance. Twenty fingerprint bands, only two of which had shown trait-associated gradients in phase I, were identified by the animal model analysis of the progeny test as QTL linked (P < or = 0.05) to specific traits of growth, reproduction and egg quality. These 20 bands warrant further study as potentially valuable molecular markers for QTL.